Downhole imaging tools are conventional in wireline applications. Such wireline tools typically create images by sending large quantities of azimuthally sensitive logging data uphole via a high-speed data link (e.g., a cable). Further, such wireline tools are typically stabilized and centralized in the borehole and include multiple (often times six or more) sensors extending outward from the tool into contact (or near contact) with the borehole wall. It will be appreciated by those of ordinary skill in the art that such wireline arrangements are not suitable for typical logging while drilling (LWD) applications. In particular, communication bandwidth with the surface would typically be insufficient during LWD operations to carry large amounts of image-related data. Further, LWD tools are generally not centralized or stabilized during operation and thus require more rugged sensor arrangements.
LWD tools commonly make use of the rotation (turning) of the tool (and therefore the LWD sensors) in the borehole to obtain measurements in multiple azimuthal directions. Depending on the sampling interval and the total sampling time, a large volume of data may result that spans substantially the entire azimuthal range. Due in large part to the limited conventional communication bandwidth between a BHA and the surface, as well as limited conventional downhole data storage capacity, the sensor data must typically undergo significant quantity reduction. This process of data reduction is sometimes collectively referred to in the art as binning or sectorization.
For example, U.S. Pat. No. 5,473,158 to Holenka et al discloses a method in which sensor data (e.g., neutron count rate) is grouped by quadrant about the circumference of the borehole. U.S. Pat. Nos. 6,307,199 to Edwards et al and 6,584,837 to Kurkoski disclose similar methods. For example, Kurkoski discloses a method for obtaining a binned azimuthal density of the formation. In the disclosed method, gamma ray counts are grouped into azimuthal sectors (bins) typically covering 45 degrees in azimuth. Accordingly, a first sector may include data collected when the sensor is positioned at an azimuth in the range from about 0 to about 45 degrees, a second sector may include data collected when the sensor is positioned at an azimuth in the range from about 45 to about 90 degrees, and so on. U.S. Pat. No. 6,619,395 to Spross discloses a methodology in which each sensor measurement is mathematically weighted based on a standoff measurement. This weighted data is then binned as described above.
While binning techniques, such as those described above, have been utilized in commercial LWD applications, both real-time and memory LWD images are often coarse or grainy (and therefore of poor quality) and in need of improvement. For example, when the number of bins is small (e.g., quadrants or octants), conventional binning strongly distorts the high-frequency components of the data, which can result in aliasing. When the number of bins is large (e.g., 32 or more), there may not be enough data points for each bin to generate a stable (low noise) output.
Commonly assigned U.S. Pat. Nos. 7,027,926 and 7,403,857 to Haugland disclose a technique in which LWD sensor data is convolved with a one-dimensional window function or a predetermined mathematical filter. This approach advantageously provides for superior image resolution and noise rejection as compared with the previously described conventional binning techniques and in particular tends to reduce the aforementioned aliasing problem. While such “windowing” techniques represent a significant advantage over conventional binning, there remains a need for further improved methods of forming LWD borehole images.